Being an efficient method of information fusion

multisensor image fusion has been used in many fields such as machine vision

medical diagnosis

military applications and remote sensing. In this paper

PCNN is introduced in this research field for its interesting properties in image processing

including segmentation

target recognition et al.

and a multisensor image fusion scheme based on modified PCNN is proposed. The basic idea of the scheme is to segment all different input images by PCNN and to use this segmentation to guide the fusion process. At the same time

a new region feature

which emphasized the salience of target regions and its neighbors is proposed. Focusing on the famous difficult problem of PCNN

how to determine PCNN parameters adaptively

an adaptive PCNN parameters determination algorithm is also presented in this paper. Experimental results demonstrate that the proposed fusion scheme outperforms the multiscale decomposition based fusion approaches

both in visual effect and objective evaluation criteria. It avoids some of the well-known problems in pixel-level fusion such as blurring effects and high sensitivity to noise

particularly when there is mis-registration of the source images. The research fruits have certain value on the theory research and practical application of PCNN.